2004
DOI: 10.3133/sir20045121
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Evaluation of conceptual models of natural organic matter (humus) from a consideration of the chemical and biochemical processes of humification

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Cited by 74 publications
(54 citation statements)
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“…Whether NOM is chemically a true macromolecular entity or a supramolecular assemblage of smaller molecular fragments held together by relatively weak non-covalent interactions (primarily electrostatic and hydrogen-bonding) is still under discussion. 2,3,[25][26][27][28] Recent experimental results strongly support the supramolecular view . [29][30][31] Modeling approaches relying only on an averaged structural and compositional 5 representation of NOM are currently successful in accurately predicting the ion binding and aggregation capabilities of NOM, as well as its other functional characteristics.…”
Section: Introductionsupporting
confidence: 53%
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“…Whether NOM is chemically a true macromolecular entity or a supramolecular assemblage of smaller molecular fragments held together by relatively weak non-covalent interactions (primarily electrostatic and hydrogen-bonding) is still under discussion. 2,3,[25][26][27][28] Recent experimental results strongly support the supramolecular view . [29][30][31] Modeling approaches relying only on an averaged structural and compositional 5 representation of NOM are currently successful in accurately predicting the ion binding and aggregation capabilities of NOM, as well as its other functional characteristics.…”
Section: Introductionsupporting
confidence: 53%
“…2,3,[26][27][28] The TNB model fragment used in our simulations contains three carboxylic groups, three carbonyl groups, two phenolic groups, two amine groups, and four other R-OH alcohol groups and has a total molecular weight of 753 Da. [38][39][40] The size, composition, molecular weight, degree of aromaticity, and total charge density of this model are in good agreement with available experimental characterization of NOM 26,27,29 , the results of computer assisted 3-D structure elucidation, 42 and stochastic biogeochemical modeling.…”
Section: Computational Methods and Detailsmentioning
confidence: 99%
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“…The molar flow concentrations of the simulated feed, desired observed product, and modeled prediction for the product composition are listed in Table 10. [18], [19], [20], [24], [25], [26], [27] 13.2 45.6 cellulose x ↔ 3x glycolaldehyde [19], [20], [25] The solution to the objective function in KME tunes the parameters to appropriately fit the desired product composition. As discussed in previous reports, the same procedure is followed for true experimental data and corresponding microkinetic reaction network.…”
Section: Engineering Designmentioning
confidence: 99%